arXiv subjects

Yanbo Pang

Publications and source records attributed to Yanbo Pang.

3 recordsLinked to original sources

arXiv2025

CBMC-V3: A CNS-inspired Control Framework Towards Agile Manipulation with SNN

As robotic arm applications expand beyond traditional industrial settings into service-oriented domains such as catering, household and retail, existing control algorithms struggle to achieve the level of agile manipulation required in unstructured environments characterized by dynamic trajectories, unpredictable interactions, and diverse objects. This paper presents a biomimetic control framework based on Spiking Neural Network (SNN), inspired by the human Central Nervous System (CNS), to address these challenges. The proposed framework comprises five control modules-cerebral cortex, cerebellum, thalamus, brainstem, and spinal cord-organized into three hierarchical control levels (first-order, second-order, and third-order) and two information pathways (ascending and descending). All modules are fully implemented using SNN. The framework is validated through both simulation and experiments on a commercial robotic arm platform across a range of control tasks. The results demonstrate that the proposed method outperforms the baseline in terms of agile motion control capability, offering a practical and effective solution for achieving agile manipulation.

cs.RO↗

arXiv2024

Explainable Hierarchical Urban Representation Learning for Commuting Flow Prediction

Commuting flow prediction is an essential task for municipal operations in the real world. Previous studies have revealed that it is feasible to estimate the commuting origin-destination (OD) demand within a city using multiple auxiliary data. However, most existing methods are not suitable to deal with a similar task at a large scale, namely within a prefecture or the whole nation, owing to the increased number of geographical units that need to be maintained. In addition, region representation learning is a universal approach for gaining urban knowledge for diverse metropolitan downstream tasks. Although many researchers have developed comprehensive frameworks to describe urban units from multi-source data, they have not clarified the relationship between the selected geographical elements. Furthermore, metropolitan areas naturally preserve ranked structures, like cities and their inclusive districts, which makes elucidating relations between cross-level urban units necessary. Therefore, we develop a heterogeneous graph-based model to generate meaningful region embeddings at multiple spatial resolutions for predicting different types of inter-level OD flows. To demonstrate the effectiveness of the proposed method, extensive experiments were conducted using real-world aggregated mobile phone datasets collected from Shizuoka Prefecture, Japan. The results indicate that our proposed model outperforms existing models in terms of a uniform urban structure. We extend the understanding of predicted results using reasonable explanations to enhance the credibility of the model.

cs.LG↗

arXiv2022

Pseudo-PFLOW: Development of nationwide synthetic open dataset for people movement based on limited travel survey and open statistical data

People flow data are utilized in diverse fields such as urban and commercial planning and disaster management. However, people flow data collected from mobile phones, such as using global positioning system and call detail records data, are difficult to obtain because of privacy issues. Even if the data were obtained, they would be difficult to handle. This study developed pseudo-people-flow data covering all of Japan by combining public statistical and travel survey data from limited urban areas. This dataset is not a representation of actual travel movements but of typical weekday movements of people. Therefore it is expected to be useful for various purposes. Additionally, the dataset represents the seamless movement of people throughout Japan, with no restrictions on coverage, unlike the travel surveys. In this paper, we propose a method for generating pseudo-people-flow and describe the development of a "Pseudo-PFLOW" dataset covering the entire population of approximately 130 million people. We then evaluated the accuracy of the dataset using mobile phone and trip survey data from multiple metropolitan areas. The results showed that a coefficient of determination of more than 0.5 was confirmed for comparisons regarding population distribution and trip volume.

physics.soc-ph↗